在心理治疗中使用大型语言模型的计算和伦理考虑.
Renwen Zhang1, Han Meng2, Marion Neubronner3
1Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore.
Nature computational science
|October 10, 2025
概括
大型语言模型 (LLM) 为心理治疗提供了潜力,但它们的作用需要系统的理解. 这种观点提出了法学士角色的分类,解决了心理健康保健中的关键计算和伦理挑战.
科学领域:
- 精神病学和心理健康 精神病学和心理健康
- 医疗保健中的人工智能
- 计算心理学 计算心理学
背景情况:
- 大型语言模型 (LLM) 显示出改善心理治疗可访问性,个性化和参与度的希望.
- 目前缺乏对心理医疗保健中的特定LLM角色的全面了解.
研究的目的:
- 提出一种新的分类法,对LLM在心理治疗中的角色进行分类.
- 根据AI自主性和情感参与,划分六个不同的LLM角色.
- 识别和讨论与心理健康的LLM整合相关的关键计算和伦理挑战.
主要方法:
- 关于LLMs和心理治疗的当前文献的概念分析和合成.
- 基于两个关键维度的分类学发展:人工智能自主性和情感参与.
- 识别相关的计算和伦理方面的考虑.
主要成果:
- 一项拟议的分类法概述了LLM在心理治疗中的六个具体角色.
- 发现的关键挑战包括情绪识别,记忆保留,隐私和情绪依赖.
- 提供了解决这些挑战的建议.
结论:
- 法律学士课程为增强心理治疗提供了显著的机会.
- 系统的框架和对伦理和计算挑战的仔细考虑对于负责任的LLM在精神卫生保健中的实施至关重要.
- 需要进一步的研究,以在治疗环境中驾人工智能的复杂性.
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